package com.xujianlong.day04;

import org.apache.flink.api.common.RuntimeExecutionMode;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.assigners.TumblingEventTimeWindows;
import org.apache.flink.streaming.api.windowing.assigners.TumblingProcessingTimeWindows;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.util.Collector;

public class Flink09_TimeWindow_Tumbing {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        env.setRuntimeMode(RuntimeExecutionMode.STREAMING);

        DataStreamSource<String> dataStreamSource = env.socketTextStream("hadoop102", 9999);

        SingleOutputStreamOperator<Tuple2<String, Long>> flatMap = dataStreamSource.flatMap(new FlatMapFunction<String, Tuple2<String, Long>>() {
            @Override
            public void flatMap(String s, Collector<Tuple2<String, Long>> collector) throws Exception {
                String[] words = s.split(" ");
                for (String word : words) {
                    collector.collect(Tuple2.of(word, 1L));
                }
            }
        });

        flatMap.keyBy(0).window( TumblingProcessingTimeWindows.of(Time.seconds(3))).sum(1).print();

        env.execute();
    }
}
